Process engineering involves the design and operation of a wide variety of processing plants and processes carried out therein. Such processes include, but are not limited to, chemical, petrochemical, refining, pharmaceutical, polymer, plastics and other process industries. In process engineering, a plethora of computer-based tools are employed by engineers to develop and evaluate new processes, design and retrofit plants, and optimize the operation of existing plants. For example, it is typical for several dozen separate engineering design tools to be used solely during the front-end engineering design phase of a new plant design.
Engineering tools tend to be developed to address a specific aspect of the entire process plant; as a result each different tool typically manages its internal engineering data using different definitions, formats, and schemas. As a result, efficient exchange of data between disparate engineering tools, although highly desirable, is very difficult in practice. This leads to handover inefficiencies, errors and rework, and lost opportunity to re-use engineering project knowledge, i.e. between the plant design and operations phases.
Within the past decade there has been growing recognition of the potential use of engineering database systems for the management of process data and the integration of disparate engineering tools. Typical implementations are developed by linking engineering tools to homegrown proprietary databases and data models using proprietary interfaces.
Similarly, once a plant is built, there is a need to implement computer programs that monitor and optimize plant operation or enable access to equipment, materials, instruments, operating procedures, maintenance orders, or other information about the plant. Until now, the process of implementing such computer programs for use in plant operations has been a manual entry of data and manual search for information stored in many systems.
This means that in the plant operation there is no use of the data that was generated during engineering design (or vice versa, no use of data generated during plant operation in engineering design). In addition, manual search for plant information through disparate computer systems creates a lot of inefficiencies and errors (e.g. wrong version of documents on specific topic is retrieved).
The growing experience of practitioners in this area has raised a number of practical problems:
Scope limitations: Data models developed to support specific engineering tools or engineering phases are limited to the narrow scope of those tools. For example, a data model developed to support process simulation tools does not have the scope to support plant pipe line-sizing tools; a data model developed to support plant equipment maintenance does not have the scope to support detailed mechanical equipment design. The use of such data models beyond their original intended scope of application is problematic.
Complexity: Attempts to support a wider scope of application will lead to more complex data models; for example, concepts of inheritance, parts, and hierarchy are needed to adequately model process equipment. The required complexity of the data models makes it practically infeasible for non-expert engineers to access useful data.
Data portability limitations: Proprietary data models developed from different sources will differ widely in formats, terminology and schemas. These wide differences make it practically infeasible to exchange data between systems that were developed independently, without prohibitively expensive efforts to map the two data models.
Maintainability: Engineering systems need to evolve over time, to accommodate new tools and uses. This will often require significant data model changes, which will in turn require re-mapping and re-linking of all of the engineering tools in the system. Maintenance of constantly evolving engineering systems is extremely costly.
Inconsistent data used in engineering design and in plant operations: Since an existing plant is constantly being modified, it is practically impossible through a manual data entry to keep an updated set of data to be used for engineering design.
As the plant matures, there is an accumulation of an ever increasing amount of operating procedures, knowledge about best operating conditions, performance, maintenance procedures, and other information. Efficient access to all information related to a particular equipment, instrument, material, process unit, entire plant, enterprise, etc. is essential for rapid information review to enable agile decision making.
Given the above, there is a need for improvement in the methodology and systems used for managing plant process and operations data.